{"id":"https://openalex.org/W1532890487","doi":"https://doi.org/10.1109/jstsp.2015.2497211","title":"Langevin and Hamiltonian Based Sequential MCMC for Efficient Bayesian Filtering in High-Dimensional Spaces","display_name":"Langevin and Hamiltonian Based Sequential MCMC for Efficient Bayesian Filtering in High-Dimensional Spaces","publication_year":2015,"publication_date":"2015-11-02","ids":{"openalex":"https://openalex.org/W1532890487","doi":"https://doi.org/10.1109/jstsp.2015.2497211","mag":"1532890487"},"language":"en","primary_location":{"id":"doi:10.1109/jstsp.2015.2497211","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2015.2497211","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1504.05715","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075184549","display_name":"Fran\u00e7ois Septier","orcid":"https://orcid.org/0000-0001-5931-6091"},"institutions":[{"id":"https://openalex.org/I205703379","display_name":"Institut Mines-T\u00e9l\u00e9com","ror":"https://ror.org/025vp2923","country_code":"FR","type":"facility","lineage":["https://openalex.org/I205703379"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I4210115519","display_name":"Centre de Recherche en Informatique","ror":"https://ror.org/020cdve92","country_code":"FR","type":"facility","lineage":["https://openalex.org/I190752583","https://openalex.org/I2746051580","https://openalex.org/I4210091621","https://openalex.org/I4210115519","https://openalex.org/I70768539"]},{"id":"https://openalex.org/I4387153239","display_name":"Centre de Recherche en Informatique, Signal et Automatique de Lille","ror":"https://ror.org/05vrs3189","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I2279609970","https://openalex.org/I4387153239","https://openalex.org/I7454413"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Francois Septier","raw_affiliation_strings":["Institut Mines-T\u00e9l\u00e9com/T\u00e9l\u00e9com Lille/CRIStAL UMR CNRS 9189, Villeneuve d'ascq, France","Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189","Institut TELECOM/TELECOM Lille1"],"affiliations":[{"raw_affiliation_string":"Institut Mines-T\u00e9l\u00e9com/T\u00e9l\u00e9com Lille/CRIStAL UMR CNRS 9189, Villeneuve d'ascq, France","institution_ids":["https://openalex.org/I205703379","https://openalex.org/I1294671590"]},{"raw_affiliation_string":"Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189","institution_ids":["https://openalex.org/I4210115519","https://openalex.org/I4387153239"]},{"raw_affiliation_string":"Institut TELECOM/TELECOM Lille1","institution_ids":["https://openalex.org/I205703379"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087616647","display_name":"Gareth W. Peters","orcid":"https://orcid.org/0000-0003-2768-8979"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gareth W. Peters","raw_affiliation_strings":["Department of Statistical Science, University College of London, UK","University College of London [London]"],"affiliations":[{"raw_affiliation_string":"Department of Statistical Science, University College of London, UK","institution_ids":[]},{"raw_affiliation_string":"University College of London [London]","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5075184549"],"corresponding_institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I205703379","https://openalex.org/I4210115519","https://openalex.org/I4387153239"],"apc_list":null,"apc_paid":null,"fwci":6.6724,"has_fulltext":false,"cited_by_count":64,"citation_normalized_percentile":{"value":0.96626252,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"10","issue":"2","first_page":"312","last_page":"327"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.7626972198486328},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6692229509353638},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.5207210183143616},{"id":"https://openalex.org/keywords/hamiltonian","display_name":"Hamiltonian (control theory)","score":0.5091308951377869},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48804914951324463},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.4514235854148865},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3873118758201599},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3503855764865875},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3401449918746948},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3376308083534241},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.30377739667892456},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.25544342398643494}],"concepts":[{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.7626972198486328},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6692229509353638},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.5207210183143616},{"id":"https://openalex.org/C130787639","wikidata":"https://www.wikidata.org/wiki/Q5645293","display_name":"Hamiltonian (control theory)","level":2,"score":0.5091308951377869},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48804914951324463},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4514235854148865},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3873118758201599},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3503855764865875},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3401449918746948},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3376308083534241},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.30377739667892456},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.25544342398643494}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/jstsp.2015.2497211","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2015.2497211","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1504.05715","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1504.05715","pdf_url":"https://arxiv.org/pdf/1504.05715","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:HAL:hal-01238978v1","is_oa":false,"landing_page_url":"https://imt.hal.science/hal-01238978","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Signal Processing, 2016, &#x27E8;10.1109/JSTSP.2015.2497211&#x27E9;","raw_type":"Journal articles"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1504.05715","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1504.05715","pdf_url":"https://arxiv.org/pdf/1504.05715","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":87,"referenced_works":["https://openalex.org/W171373254","https://openalex.org/W621546036","https://openalex.org/W1480561599","https://openalex.org/W1483307070","https://openalex.org/W1513008779","https://openalex.org/W1542184596","https://openalex.org/W1545319692","https://openalex.org/W1556278552","https://openalex.org/W1558572410","https://openalex.org/W1565709818","https://openalex.org/W1567512734","https://openalex.org/W1628017834","https://openalex.org/W1670531616","https://openalex.org/W1724863204","https://openalex.org/W1741551153","https://openalex.org/W1822984620","https://openalex.org/W1840380860","https://openalex.org/W1969248194","https://openalex.org/W1981514681","https://openalex.org/W1985093013","https://openalex.org/W1986776366","https://openalex.org/W1991233316","https://openalex.org/W2022629036","https://openalex.org/W2040196349","https://openalex.org/W2040975855","https://openalex.org/W2042621213","https://openalex.org/W2048971218","https://openalex.org/W2055600978","https://openalex.org/W2055936398","https://openalex.org/W2057291289","https://openalex.org/W2059448777","https://openalex.org/W2062758445","https://openalex.org/W2075749231","https://openalex.org/W2076538312","https://openalex.org/W2078413699","https://openalex.org/W2082399300","https://openalex.org/W2098613108","https://openalex.org/W2100397110","https://openalex.org/W2105934661","https://openalex.org/W2113926057","https://openalex.org/W2114656557","https://openalex.org/W2118064230","https://openalex.org/W2123487311","https://openalex.org/W2124717147","https://openalex.org/W2126736494","https://openalex.org/W2127579861","https://openalex.org/W2131598171","https://openalex.org/W2135254894","https://openalex.org/W2140552995","https://openalex.org/W2143225719","https://openalex.org/W2147035977","https://openalex.org/W2148178414","https://openalex.org/W2150951085","https://openalex.org/W2151253365","https://openalex.org/W2153355083","https://openalex.org/W2153811005","https://openalex.org/W2168634963","https://openalex.org/W2173476375","https://openalex.org/W2282580722","https://openalex.org/W2338138852","https://openalex.org/W2467033644","https://openalex.org/W2478027467","https://openalex.org/W2564813814","https://openalex.org/W2953328789","https://openalex.org/W2954040150","https://openalex.org/W2962703949","https://openalex.org/W3021966610","https://openalex.org/W3100586012","https://openalex.org/W3102676823","https://openalex.org/W3104580728","https://openalex.org/W3122858766","https://openalex.org/W4233487859","https://openalex.org/W4240105987","https://openalex.org/W4244486013","https://openalex.org/W4244695582","https://openalex.org/W4285719527","https://openalex.org/W4292691288","https://openalex.org/W4388085068","https://openalex.org/W6628738788","https://openalex.org/W6633901960","https://openalex.org/W6637697042","https://openalex.org/W6674975652","https://openalex.org/W6677822847","https://openalex.org/W6682686748","https://openalex.org/W6695533491","https://openalex.org/W6697323721","https://openalex.org/W6730934883"],"related_works":["https://openalex.org/W3087071515","https://openalex.org/W4283077537","https://openalex.org/W2999603699","https://openalex.org/W2902858271","https://openalex.org/W2464065341","https://openalex.org/W2947536360","https://openalex.org/W3086697448","https://openalex.org/W1987558550","https://openalex.org/W2968689489","https://openalex.org/W4302573481"],"abstract_inverted_index":{"Nonlinear":[0],"non-Gaussian":[1],"state-space":[2],"models":[3],"arise":[4],"in":[5,8,105],"numerous":[6],"applications":[7],"statistics":[9],"and":[10,21,102],"signal":[11],"processing.":[12],"In":[13,50],"this":[14,38,51],"context,":[15],"one":[16],"of":[17,58,87,99,113],"the":[18,26,63,85,97,110,120],"most":[19],"successful":[20],"popular":[22],"approximation":[23],"techniques":[24],"is":[25],"Sequential":[27,64],"Monte":[28,67],"Carlo":[29,68],"(SMC)":[30],"algorithm,":[31],"also":[32],"known":[33],"as":[34],"particle":[35],"filtering.":[36],"Nevertheless,":[37],"method":[39],"tends":[40],"to":[41,46,76,107,128],"be":[42],"inefficient":[43],"when":[44],"applied":[45],"high":[47],"dimensional":[48],"problems.":[49],"paper,":[52],"we":[53,90],"focus":[54],"on":[55,96],"another":[56],"class":[57,86],"sequential":[59],"inference":[60],"methods,":[61],"namely":[62],"Markov":[65],"Chain":[66],"(SMCMC)":[69],"techniques,":[70],"which":[71],"represent":[72],"a":[73,81],"promising":[74],"alternative":[75],"SMC":[77],"methods.":[78],"After":[79],"providing":[80],"unifying":[82],"framework":[83],"for":[84],"SMCMC":[88],"approaches,":[89],"propose":[91],"novel":[92],"efficient":[93],"strategies":[94],"based":[95],"principle":[98],"Langevin":[100],"diffusion":[101],"Hamiltonian":[103],"dynamics":[104],"order":[106],"cope":[108],"with":[109],"increasing":[111],"number":[112],"high-dimensional":[114],"applications.":[115],"Simulation":[116],"results":[117],"show":[118],"that":[119],"proposed":[121],"algorithms":[122],"achieve":[123],"significantly":[124],"better":[125],"performance":[126],"compared":[127],"existing":[129],"algorithms.":[130]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":14},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
